Co-optimization method to improve lateral resolution in photoacoustic computed tomography

Adaptive polarization photoacoustic computed tomography for biological anisotropic tissue imaging

Most photoacoustic computed tomography (PACT) systems usually ignore the anisotropy of the tissue absorption coefficient, which will lead to the lack of information in reconstructed images. In this work, the effect is addressed of the possible optical absorption anisotropy of tissue on PACT images. The functional relationship is derived between the photoacoustic response and the polarization angle of the excitation light. An adaptive polarized light photoacoustic imaging (AP-PACT) approach is proposed and shown to make up for the lack of imaging information and achieve optimal image contrast when imaging samples with anisotropic optical absorption, by utilizing the standard deviation of photoacoustic response as the feedback signal in an adaptive data acquisition process. The method is implemented both on phantom and in vitro experiments, which show that AP-PACT can recover anisotropic absorption-related information from reconstructed images and thus significantly improve their quality.

The influences of finite aperture size in photoacoustic computed tomography

In photoacoustic computed tomography (PACT), the "finite aperture effect" is often characterized as a tangential resolution that increases proportionally with the distance from the rotation center. However, this conclusion is based on the inaccurate point-detector assumption used in image reconstruction. In this study, we appropriately modeled the finite size of the acoustic detector in the back-projection (BP) based image reconstruction to improve the accuracy of the time delay calculation and systematically investigated its effects. Our results showed that the main effect of the finite aperture size is the creation of a limited high-quality imaging region (HQIR) around the scanning center, due to the directional sensitivity of the detector. We also demonstrated that the "finite aperture effect" can reduce the optimal number of detectors required for spatial anti-aliasing. These new findings provide novel perspectives for optimizing PACT systems and corresponding reconstruction methods.

Signal restoration algorithm for photoacoustic imaging systems

In a photoacoustic (PA) imaging system, the detectors are bandwidth-limited. Therefore, they capture PA signals with some unwanted ripples. This limitation degrades the resolution/contrast and induces sidelobes and artifacts in the reconstructed images along the axial direction. To compensate for the limited bandwidth effect, we present a PA signal restoration algorithm, where a mask is designed to extract the signals at the absorber positions and remove the unwanted ripples. This restoration improves the axial resolution and contrast in the reconstructed image. The restored PA signals can be considered as the input of the conventional reconstruction algorithms (e.g., Delay-and-sum (DAS) and Delay-multiply-and-sum (DMAS)). To compare the performance of the proposed method, DAS and DMAS reconstruction algorithms were performed with both the initial and restored PA signals on numerical and experimental studies (numerical targets, tungsten wires, and human forearm). The results show that, compared with the initial PA signals, the restored PA signals can improve the axial resolution and contrast by 45% and 16.1 dB, respectively, and suppress background artifacts by 80%.